تخمين نگاره هاي چاه پيمايي با استفاده از نشانگرهاي لرزه اي چندگانه در سازندآسماري ، ميدان نفتي هنديجان

Prediction of Well Log Data from Seismic Multiattribute in Asmari Formation, Hendijan Oil Field

Well logs are one of the important tools in reservoir characterization. Parameters such as porosity, volume of shale, water saturation, permeability, lithology and production zones could be computed from processing and interpreting of well logs. For many reasons, such as incomplete logging in old wells, destruction of logs due to inappropriate data storage and measurement errors due to problems with logging apparatus or hole conditions, log suites are either incomplete or unreliable. Considering coverage and continuity of seismic data, log estimation in each location of reservoir by using seismic data, not only before the drilling but also after it will be applied and invaluable. So that using the predicted wells log from seismic data, reservoir evaluation and assessment over the seismic data coverage is possible. In this research, a formulation is established between well log data including sonic, density, porosity and their corresponding seismic attributes at well location using neural networks. For this purpose, optimal input seismic attributes were obtained using a forward stepwise regression. Predicted well logs using seismic data could be used for reservoir parameters evaluation and reducing risks of future exploration and fieldsʹ development.